Tsung-Chien (Jonathan) Lu
Graduated: June 14, 2019
Using Smart Watches to Facilitate High Quality Cardiopulmonary Resuscitation for Patients with Cardiac Arrest
Cardiopulmonary resuscitation (CPR) quality affects survival after cardiac arrest. Past studies have shown that both healthcare professionals and laypersons often perform CPR at inadequate rates and depths, and CPR quality can be improved with adequate feedback. This dissertation sought to develop a wearable application (app) with real-time feedback by using a commercially available smartwatch to facilitate the delivery of high-quality CPR. First I conducted a systematic review on healthcare applications of smartwatches. The results find that most of the identified smartwatch studies focused on applications involving health monitoring for the elderly, and there are potential for smartwatch use in clinical settings. The second step is to develop a smartwatch app with real-time audiovisual feedback on CPR quality. By using the sensor data collected from the built-in accelerometer of the smartwatch, two novel algorithms capable of estimating chest compression rate and depth were developed and validated. User-centered design was adopted during the smartwatch interface development of the prototype and usability test was conducted for the final app. Finally, to evaluate if a smartwatch app with real-time audiovisual feedback could improve CPR quality, 80 Emergency Department (ED) professionals were recruited and randomly allocated to either the intervention group wearing a smartwatch with the preinstalled app, or to a control group. All participants were asked to perform a two-minute CPR on a manikin at 30:2 compression-ventilation ratio. The results show that chest compressions tend to be too fast and too shallow without feedback and CPR quality can be improved with feedback from a smartwatch. This work is a great example of applying modern information technology to improve the quality of healthcare. Although it is a simulation study performed on a manikin, it has great potential to be utilized in the clinical settings.
Last Known Position:
Anne Turner, Cynthia Dougherty, George Demiris, Hendrika Meischke